Data processing: generic control systems or specific application – Generic control system – apparatus or process – Multiple modes
Reexamination Certificate
2002-03-22
2003-12-09
Patel, Ramesh (Department: 2121)
Data processing: generic control systems or specific application
Generic control system, apparatus or process
Multiple modes
C700S031000, C706S025000
Reexamination Certificate
active
06662059
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to a characteristic adjusting method in a process of manufacturing products.
2. Description of the Related Art
A large number of steps are incorporated into a process of manufacturing products, and a step of adjusting a characteristic is provided in the process of manufacturing products. When a processing condition for controlling a characteristic of products is imparted into the step of adjusting a characteristic thereof, the characteristic can be often incorporated into the products when the products are finished. For example, in the manufacturing process shown in
FIG. 6
, after steps
1
to n−
1
have been successively executed, the processing condition for controlling a characteristic is imparted into step n which is a step for adjusting a characteristic. Further, after step n+
1
etc. have been successively executed, the characteristic of the finished product is inspected. For example, in the case of ceramic products, heat treatment corresponds to the process for adjusting a characteristic, and the heat treatment condition in the step of heat treatment corresponds to the processing condition for controlling a characteristic. In this case, the resultant characteristic obtained in characteristic inspection is fed back to the characteristic adjusting step, so that the processing condition for controlling a characteristic is changed in the step and the resultant characteristic in the characteristic inspection is made to agree with a target value.
However, according to the above method, following problems may be encountered. The resultant product characteristic that does not agree with a target value is confirmed in a final characteristic inspection step, and a correcting action is started after the confirmation in the final characteristic inspection step. When a lead time exists between the characteristic adjusting step (step n) and the characteristic inspection step, all products, which have been produced in a time period corresponding to the lead time, do not agree with the target value.
On the other hand, and different from the above method in which a resultant characteristic obtained in a characteristic inspection is fed back to the processing condition for controlling the characteristic, a method of predicting the product characteristic is disclosed in Japanese Unexamined Patent Publication Nos. 10-187206 and 5-204407. For example, according to the technique disclosed in Japanese Unexamined Patent Publication No. 10-187206, a process is predicted on the basis of a mathematical model (theoretical formula) simulating the process of manufacturing a product body to be processed. In this case, in order to enhance the prediction accuracy, an offset value is found so as to correct the mathematical model on the basis of actual processing result data, obtained in the past, which are grouped according to the type of the product body to be processed or according to the process condition. However, in the case of the above patent publication, the mathematical model (theoretical formula) is required for predicting the result of process. Therefore, unless the mathematical model is made with high accuracy, it is impossible to predict with high accuracy. Further, it can be considered that a mathematical model of a manufacturing process can not be made. This technique disclosed in the above patent publication cannot be applied to a manufacturing process, a mathematical model of which cannot be made.
According to the technique disclosed in Japanese Unexamined Patent Publication No. 5-204407, a quantity of state and a quantity of output are determined to be variables to express a state of the process, and sampling is conducted on the quantity of state and the quantity of output in a specific time period. Multiple regression analysis is conducted in the multiple regression analysis section by using sampling values from a point of time of each sampling to a point of time of a predetermined time period in the past, so that a coefficient of partial regression can be found. Then, when patterns of the coefficients of partial regression are classified by a neural network, the pattern of change in the output value of the process is predicted. However, according to the above method, the output characteristic itself of the process (system) is not predicted but only the pattern of a change is predicted. Therefore, it has been impossible to conduct a fine adjustment, that is, it is impossible to incorporate a desired characteristic into a final characteristic of the product.
SUMMARY OF THE INVENTION
The present invention has been accomplished to solve the above problems. It is an object of the present invention to provide a characteristic adjusting method in a process of manufacturing products so that a characteristic can be relatively easily incorporated into products and the accuracy of incorporation of a characteristic can be enhanced.
In the manufacturing process according to the present invention, a characteristic adjusting step for imparting a processing condition for controlling a characteristic is executed in a large number of steps, and a characteristic inspecting step is executed via at least an another step after the characteristic adjusting step. In the characteristic adjusting method of the present invention, when a general classification is made, the major steps consist of a data preparing stage, a model making stage and a model applying stage. In more detail, in the data preparing stage, a set of data, for each product lot, which includes: respective intermediate characteristics obtained in each step before the characteristic adjusting step; a processing condition for controlling the characteristic imparted in the characteristic adjusting step; and a product characteristic, in the characteristic inspecting step, obtained on the basis of the intermediate characteristics in respective steps and the processing condition for controlling the characteristic, is prepared. In the model making stage, a learning model, which expresses a causal relation when the intermediate characteristic and the processing condition for controlling the characteristic are inputted and the product characteristic is outputted, is made by using the sets of data prepared in the above stage. Further, in the model applying stage, in the characteristic adjusting step, the most appropriate processing condition for controlling the characteristic is retrieved from the intermediate characteristics obtained in the steps before the characteristic adjusting step by using the learning model made in the above stage. In the second aspect of the present invention, in this model applying stage, on the assumption of the intermediate characteristics obtained in the steps before the characteristic adjusting step, product characteristics are predicted by changing the processing condition for controlling the characteristic and a processing condition for controlling a characteristic, which is predicted to create small error in a product characteristic, is retrieved.
After all, the intermediate characteristics and the processing condition for controlling the characteristic are important factors to determine the product characteristic. Therefore, when the learning model is made from the causal relation of the intermediate characteristics and the processing condition for controlling the characteristic with the product characteristic in the characteristic inspection step, as described above and, further, when the learning model is applied to the process after that, the product characteristic, in each product manufacturing, with respect to the intermediate characteristics and the processing condition for controlling the characteristic, in each product manufacturing, can be precisely predicted. In other words, in the characteristic adjusting step, the processing condition for controlling the characteristic to obtain a desired product characteristic can be automatically and appropriately retrieved from the intermediate characteristics (the processing
Fukuhara Yasuhiro
Ito Yoshiharu
Hartman, Jr. Ronald D.
Patel Ramesh
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